
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "28"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 116 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 111 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	RF_maintenance	100.00%	60.00%	21.08%	31.89%	100.00%	0.00%	15.581668	-0.462600	11.239250	0.701760	24.955868	4.752049	20.864328	5.479297	0.3569	0.5256	-0.0510	3.711711	12.694731
2459593	RF_maintenance	100.00%	61.64%	51.38%	18.91%	100.00%	0.00%	21.695770	-0.465367	12.899859	0.329015	18.852797	7.963125	11.564714	3.211425	0.3251	0.4647	-0.0346	2.409318	7.370848
2459592	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	2.604582	-0.855442	18.893683	-0.980022	3.785170	-0.204852	-1.669230	-0.054100	0.0304	0.0306	0.0028	nan	nan
2459591	RF_maintenance	100.00%	88.11%	87.57%	11.89%	100.00%	0.00%	28.279554	-0.559114	17.797819	-0.844107	17.793993	5.895189	23.037191	0.322786	0.1656	0.2597	-0.1233	2.221713	6.516968
2459590	RF_maintenance	100.00%	90.81%	90.27%	9.19%	100.00%	0.00%	27.159170	-0.523310	13.323445	-0.452270	21.058357	8.166258	15.487611	0.204991	0.1708	0.2640	-0.1168	2.227177	5.810503
2459589	RF_maintenance	100.00%	76.18%	58.89%	10.32%	100.00%	0.00%	26.467903	1.052802	12.566846	0.093803	12.502771	9.028199	12.515554	6.746710	0.2875	0.4177	-0.0412	2.314638	7.125727
2459588	RF_maintenance	100.00%	58.89%	37.28%	14.10%	100.00%	0.00%	20.136985	-0.723114	14.337110	-0.831551	25.423566	3.987436	10.861489	2.883748	0.3789	0.5382	-0.0122	3.233452	12.129405
2459587	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	27.335896	-0.088796	24.152408	-0.522530	2.357794	0.757091	9.898716	-0.306314	nan	nan	nan	3.308413	9.658370
2459586	RF_maintenance	100.00%	91.35%	85.41%	8.65%	100.00%	0.00%	26.340622	-0.290891	8.139174	0.231659	10.027697	0.810309	14.423127	0.458543	0.1769	0.2857	-0.1146	2.192815	5.667596
2459585	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	5.098577	0.955087	3.281069	1.189037	10.545285	0.925321	0.122618	1.232055	0.0311	0.0361	0.0012	0.000000	0.000000
2459584	RF_maintenance	100.00%	89.80%	89.80%	10.20%	100.00%	0.00%	35.109399	0.751041	15.147154	3.654635	5.718850	-0.492293	4.873949	0.138634	0.1326	0.2168	-0.1257	2.737137	7.999212
2459583	RF_maintenance	100.00%	91.36%	90.22%	8.64%	100.00%	0.00%	24.335607	-0.027702	3.735640	1.829910	12.251406	3.957841	6.494426	0.169942	0.1531	0.2391	-0.1175	2.325465	6.297566
2459582	RF_maintenance	100.00%	89.73%	88.65%	10.27%	100.00%	0.00%	21.720054	-0.178113	3.160004	1.852809	12.391146	4.729559	5.077341	0.093368	0.1471	0.2330	-0.1343	2.167494	5.734860
2459581	RF_maintenance	100.00%	89.19%	88.11%	10.81%	100.00%	0.00%	28.659987	0.100683	3.484323	1.653868	11.009802	3.752788	8.461922	-0.075306	0.1609	0.2509	-0.1283	2.156037	5.296173
2459580	RF_maintenance	100.00%	87.52%	86.98%	12.48%	100.00%	0.00%	22.704173	-0.221506	3.082701	1.842379	13.359547	3.965861	8.062686	-0.089440	0.1580	0.2580	-0.1345	2.384003	6.933075
2459579	RF_maintenance	100.00%	87.52%	86.98%	12.48%	100.00%	0.00%	22.230868	-0.241271	3.926001	2.577097	10.991546	4.498497	14.567075	0.519366	0.1523	0.2489	-0.1438	2.626948	7.519827
2459578	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	2.441989	-0.649487	11.870363	-0.919478	5.902710	0.116564	4.031834	0.318276	0.0296	0.0309	0.0035	nan	nan
2459577	RF_maintenance	100.00%	83.33%	83.33%	16.67%	100.00%	0.00%	27.468375	-0.285353	2.935000	1.596880	9.905729	3.975184	7.775348	-0.184223	0.1712	0.2608	-0.1427	2.102150	4.899423
2459576	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	19.802490	0.237987	2.102832	1.646828	7.911965	2.873169	15.868209	0.313733	0.0683	0.0843	-0.0086	1.253819	1.266465
2459575	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	20.557717	-0.093073	2.503172	1.232321	4.497567	3.179595	4.265503	4.124487	0.0595	0.0644	-0.0036	0.000000	0.000000
2459574	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	20.535466	-0.041687	2.544508	1.256354	9.665708	3.425097	8.400359	0.975204	0.0774	0.1064	-0.0064	1.198846	1.208112
2459573	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	22.455253	0.384827	4.481848	2.108338	9.587584	3.446275	10.560489	0.707348	0.0651	0.0850	-0.0035	0.000000	0.000000
2459572	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	20.418892	0.636729	1.997954	1.312247	5.819952	1.914893	21.344154	1.074792	0.0648	0.0794	-0.0085	1.209770	1.218292
2459571	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	2.212743	-0.739139	12.578334	-0.945636	15.332366	5.945010	8.042351	1.094079	0.0302	0.0334	0.0063	nan	nan
2459570	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459569	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459566	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	21.097427	0.054434	3.240679	1.648514	6.278753	2.291400	7.807885	0.352472	0.0715	0.1003	-0.0073	1.071113	1.055680
2459565	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	0.532291	0.532291	0.525437	0.525437	-0.677115	-0.677115	-0.811160	-0.811160	nan	nan	nan	0.000000	0.000000
2459564	RF_maintenance	100.00%	66.51%	64.78%	32.39%	100.00%	0.00%	18.361218	0.082884	2.539356	0.634420	1.499708	1.612121	12.595992	0.272819	0.2101	0.3342	-0.1872	1.905335	4.593308
2459563	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459562	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459561	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459560	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459559	RF_maintenance	100.00%	74.01%	70.77%	25.99%	100.00%	0.00%	20.310902	0.360047	1.240711	1.040831	6.144275	-0.524448	14.668386	0.708908	0.2005	0.3417	-0.1680	1.808202	4.060682
2459558	RF_maintenance	100.00%	73.47%	71.31%	26.53%	100.00%	0.00%	22.829416	0.304838	3.301877	1.346921	6.715059	1.275648	19.094148	0.989963	0.1928	0.3329	-0.1671	2.043919	5.200965
2459557	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0306	0.0360	0.0038	nan	nan
2459556	RF_maintenance	100.00%	73.55%	71.39%	25.37%	100.00%	0.00%	25.609744	0.308641	3.104535	1.602830	10.997255	1.226131	43.368947	1.792879	0.2028	0.3378	-0.1606	2.081724	5.589895
2459554	RF_maintenance	-	68.61%	67.53%	31.39%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.1868	0.3076	-0.1899	nan	nan
2459553	RF_maintenance	-	66.63%	65.01%	33.37%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.1971	0.3281	-0.1869	nan	nan
2459552	RF_maintenance	100.00%	71.35%	68.11%	26.49%	100.00%	0.00%	26.540201	0.570144	4.681123	1.750895	14.703739	5.975316	11.963657	2.351530	0.2004	0.3412	-0.1664	0.938670	0.877730
2459551	RF_maintenance	100.00%	70.23%	69.15%	29.77%	100.00%	0.00%	13.801373	0.174247	1.565701	0.976366	4.327881	-0.290099	17.226599	0.812102	0.2060	0.3355	-0.1721	1.916884	4.511172
2459550	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0304	0.0394	0.0010	nan	nan
2459549	RF_maintenance	100.00%	73.51%	71.35%	26.49%	100.00%	0.00%	20.731994	0.012969	3.131917	1.260177	8.190782	1.444322	16.879293	0.997268	0.1933	0.3295	-0.1646	2.033089	5.111435
2459542	RF_maintenance	100.00%	55.70%	48.55%	40.27%	100.00%	0.00%	25.310001	-0.180367	6.528204	-0.107477	0.474603	1.498929	9.836055	0.088627	0.2671	0.4311	-0.1446	1.982324	4.470323
2459541	RF_maintenance	100.00%	55.26%	47.65%	37.58%	100.00%	0.00%	21.779384	0.186133	1.866946	1.924661	3.357423	3.292015	11.355148	4.439548	0.3161	0.4608	-0.1261	2.074615	5.479295
2459540	RF_maintenance	100.00%	61.07%	51.68%	34.00%	100.00%	0.00%	19.850603	0.243803	1.542879	0.726669	2.947591	0.125511	4.919430	1.386437	0.2619	0.4261	-0.1127	1.852981	4.467177
2459536	RF_maintenance	100.00%	53.37%	51.89%	46.63%	100.00%	0.00%	32.028061	1.268165	2.048365	2.669985	9.230707	2.107926	28.430860	3.258863	0.1941	0.3296	-0.2093	2.720315	8.073737
2459535	RF_maintenance	100.00%	55.70%	44.07%	41.16%	100.00%	0.00%	16.304864	0.740962	1.425552	0.592199	6.706396	2.063578	8.281360	2.836291	0.2447	0.4285	-0.1471	2.004266	5.866935
2459534	RF_maintenance	100.00%	53.91%	41.39%	43.85%	100.00%	0.00%	17.064147	-0.084632	1.587978	0.447083	2.979265	0.627821	5.360867	1.135566	0.2404	0.4194	-0.1580	1.974312	5.905103
2459533	RF_maintenance	100.00%	70.96%	68.23%	29.04%	100.00%	0.00%	24.913265	-0.328821	2.632352	0.656920	5.912531	3.449269	10.280733	1.661652	0.1796	0.3197	-0.1800	2.022835	5.294122
2459532	RF_maintenance	100.00%	64.77%	64.21%	35.23%	100.00%	0.00%	27.506531	-0.191332	3.174205	1.724107	8.502891	3.688232	14.521472	0.706460	0.1832	0.3174	-0.1918	2.186205	6.254740
2459530	RF_maintenance	100.00%	58.86%	56.48%	41.14%	100.00%	0.00%	15.749987	-0.301071	1.124171	0.545562	1.843937	0.327843	10.660443	2.893926	0.1989	0.3365	-0.1975	2.154609	5.978724
2459527	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	RF_maintenance	100.00%	0.00%	0.00%	100.00%	100.00%	0.00%	20.972754	-0.355570	5.071026	1.041331	13.293234	7.864176	10.906474	0.789754	0.4269	0.6498	-0.1868	0.000000	0.000000
2459523	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	32.088761	1.957204	2.093728	1.427104	11.026141	6.478842	22.934362	1.482625	nan	nan	nan	2.769016	5.667242
2459522	RF_maintenance	100.00%	100.00%	86.36%	0.00%	100.00%	0.00%	19.565290	1.603706	1.618253	2.265947	9.519147	9.722257	24.630221	2.004364	0.2235	0.3616	-0.0538	2.579223	5.177396
2459513	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	2.602718	-0.716555	12.499305	-0.761834	11.672984	0.539808	35.045165	0.343556	0.0339	0.0366	0.0004	nan	nan
2459508	RF_maintenance	100.00%	0.00%	0.00%	100.00%	100.00%	0.00%	15.348423	0.826077	3.980527	0.942446	4.979501	4.542793	12.917530	6.750240	0.5751	0.7548	-0.1033	0.000000	0.000000
2459505	RF_maintenance	100.00%	0.00%	0.00%	38.60%	100.00%	0.00%	15.113712	5.313573	0.478305	3.489898	14.877358	8.048745	42.431582	3.602902	0.4706	0.7030	0.0448	11.371032	50.404427
2459503	RF_maintenance	100.00%	22.04%	16.67%	77.96%	100.00%	0.00%	12.034685	0.978967	3.791817	1.349052	9.986187	3.515392	24.950750	0.750712	0.2581	0.4338	-0.2484	0.000000	0.000000
2459501	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	17.124223	0.314561	2.678138	0.386031	12.854449	1.887557	23.306156	0.757302	0.1264	0.1539	-0.0148	0.000000	0.000000
2459500	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	14.834465	0.026657	5.552599	-0.390640	6.465305	0.554046	13.678892	-0.071192	0.1291	0.1557	-0.0167	0.000000	0.000000
2459499	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	13.981973	1.049682	5.896755	0.492803	7.497306	1.120766	39.782589	9.174092	0.1379	0.1787	-0.0093	0.000000	0.000000
2459498	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	11.210502	0.884570	4.025709	0.374529	9.763124	0.537528	36.824505	0.887438	0.1281	0.1494	-0.0208	0.000000	0.000000
2459497	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	11.749133	1.447158	2.845235	0.407724	12.841295	0.708693	25.499686	1.148529	0.1283	0.1596	-0.0219	0.000000	0.000000
2459496	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	12.808146	1.498949	3.929010	0.549246	11.428419	0.769007	21.339369	0.113637	0.1454	0.1810	-0.0225	0.000000	0.000000
2459495	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	9.837627	1.005340	3.081510	0.335566	10.698723	0.352703	25.468217	-0.053874	0.1352	0.1728	-0.0244	0.000000	0.000000
2459494	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	12.274861	0.831098	4.257523	0.086154	12.390816	0.728776	50.846036	0.746094	0.1295	0.1687	-0.0247	0.000000	0.000000
2459492	RF_maintenance	100.00%	56.45%	53.76%	43.55%	100.00%	0.00%	20.810123	0.894526	5.406811	0.889592	27.201023	0.877403	91.648951	11.178127	0.3100	0.4690	-0.1276	1.060213	1.308082
2459491	RF_maintenance	100.00%	51.08%	48.39%	48.92%	100.00%	0.00%	24.154590	2.366456	5.489676	2.210418	29.231141	6.295451	35.162398	11.567614	0.4672	0.5594	-0.0748	1.588053	5.926867
2459490	RF_maintenance	100.00%	51.08%	51.08%	48.92%	100.00%	0.00%	26.513472	2.014557	5.773223	1.491427	20.816105	0.921511	47.134929	3.906856	0.2876	0.4330	-0.1527	3.218040	10.283110
2459489	RF_maintenance	100.00%	51.08%	48.39%	48.92%	100.00%	0.00%	25.097298	2.132164	5.263632	0.378491	25.612187	2.270215	44.191689	6.558572	0.3811	0.5006	-0.0993	3.332984	11.139703
2459488	RF_maintenance	100.00%	51.08%	51.08%	48.92%	100.00%	0.00%	27.624440	1.688448	3.442018	0.911480	42.072335	2.472927	132.631947	9.169055	0.3088	0.4697	-0.1267	0.000000	0.000000

Antenna Season Report Notebook¶

Antenna 28 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 28, Node 1:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 28: 2459642

Antenna 28: 2459640

Antenna 28: 2459639

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Antenna 28: 2459637

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Antenna 28: 2459609

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Antenna 28: 2459561

Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶